Magnetic resonance imaging (“MRI”) is a well-known, highly useful technique for diagnosing abnormalities in biological tissues. MRI can detect abnormalities that are difficult or impossible to detect by other techniques, without the use of x-rays or invasive procedures.
However, to date conventional MRI has not been capable enough to distinguish accurately between normal, benign, and malignant tissues. This is primarily because tissues have a number of distinguishing characteristics, which change for each patient and the tissue being monitored, and therefore a fixed threshold for classifying the tissue is not possible. Further, to sustain aggressive growth, tissues generate millions of tiny “microvessels” that increase the local blood supply around the tumor to sustain their abnormal growth.
Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a promising tool in the fight against breast cancer, prostate cancer, and other cancer types. In DCE-MRI, a contrast agent known to significantly and predictably enhance certain MRI readings, such as T1-weighted MRI readings, is injected into a patient and a time sequence of MRI volumes is acquired. This is known to significantly and predictably enhance certain MRI readings, such as T1-weighted MRI readings, As the contrast agent, commonly also termed a tracer, is transported throughout the body by the vascular system (e.g., arteries, arterioles, capillaries, veins, and other types of blood vessels), it diffuses across the vessel walls into the surrounding tissue. The surrounding tissue generally comprises (i) tissue cells and (ii) interstitial space among the tissue cells, termed extracellular extravascular space (EES). DCE-MRI may be performed by acquiring a sequence of MR images and T1 weighted MRI readings, in a time span before magnetic contrast agents/tracer are introduced into the patient's body and a time after the magnetic contrast agents are introduced. For example, a first MR image may be acquired prior to the introduction of the magnetic contrast agents, and subsequent MR images may be taken at a rate of one image per minute for a desired time period. By imaging the body in this way, a set of images may be acquired that illustrate how the magnetic contrast agent is absorbed and washed out from various portions of the patient's body. Different tissue types have different contrast agent uptake and flush properties, and so study of the resonance signal over time enables identification of the different tissue types. This absorption and washout information may be used to characterize various internal structures within the body and may provide additional diagnostic information.
To sustain aggressive growth, tissues generate millions of tiny “microvessels” that increase the local blood supply around the tumor to sustain their abnormal growth. Typically, a cancerous tissue shows a high and fast uptake because of the microvasculature which is leaky, while normal and fatty tissues show little contrast agent uptake. Contrast agent uptake curves shows that malignant tissue (a tumor) is characterized by a sharp rise and overall higher enhancement than benign, normal or fatty tissue. Uptake curves can be graphically depicted with respect to Intensity vs. Time values for tissues under observation at within a desired time period after injecting the contrast agent. These uptake curves have often been fitted using a pharmacokinetic model (a model which mathematically relates to the concentration of contrast agent in the tissue as a function of time with various physiological parameters of the tissue such as transfer constant Ktrans, also termed as permeability constant and an extracellular volume parameter Ve, etc.) in an attempt to give a physiologically relevant parameterization of the curve. Study of these curves/parameters has been proposed as a technique which could identify and characterize tumors into malignant or benign classes.
However, the results of classification of tissues are currently insufficiently reliable to provide a conclusive diagnosis. One reason for this could be that existing pharmacokinetic models require knowledge of the change in amount or concentration of contrast agent in the tissue over time. But the signal enhancement seen in the magnetic resonance image is not simply related to the amount of contrast agent in the tissue. Instead the relationship between the signal enhancement and the concentration of contrast agent in the sample is both non-linear and highly dependent on the intrinsic longitudinal relaxation time (T1 value) of the sample. The T1 value varies greatly for different types of tissue, for instance from about 175 ms for fat, 765 ms for fibrocystic tissue, 800 ms for parenchymal tissue, between 700-1000 ms for malignant tissue and 1000 ms for a fibroadenoma (all measured at 1.0 T). Also, the intrinsic T1 value varies with the machine parameters, resulting in incorrect computation of net T1 value when the contrast is given, which as a result leads to inaccurate computation of pharmacokinetic parameters that are used for tissue classification. Also, if a particular voxel is showing a high enhancement, it is difficult to conclude that whether this is due to the uptake of contrast agent or the intrinsic T1 value of the tissue. Thus, one cannot predict whether it is a physiologically-based effect (high uptake of contrast agent) or an intrinsic effect (because of the T1 value of that type of tissue).
Paper titled “Contrast-enhanced magnetic resonance imaging of the breast: the value of pharmacokinetic parameters derived from fast dynamic imaging during initial enhancement in classifying lesions” by Veltman et al discloses usage of value of pharmacokinetic parameters for characterizing breast lesions. The paper further discloses the advantage of conducting both slow and fast dynamic analysis for improvement in diagnostic performance. US 20040242994 discloses fitting a parameterized pharmaco-kinetic model of a contrast enhancement process for each voxel for representing properties of each imaged sample.
Hence, it is necessary to develop an improved method to quantify and validate errors involved in calculating pharmacokinetic parameters such as Ktrans from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) scans, improve accuracy of correct classification of benign, normal, and malignant tissues, and to develop a time efficient, reliable and reproducible diagnostic technique and tool for the measurement of Ktrans.